使用tibble::add_row、dplyr::group_split和purrr::map_dfr，您可以执行以下操作：

library(dplyr, warn = FALSE)
library(tibble)
library(purrr)

pad_rows <- function(x) {
  x |> 
    tibble::add_row(S.NO = first(x$S.NO), AGE_2 = first(x$AGE_1), .before = 1) |> 
    tibble::add_row(S.NO = last(x$S.NO), AGE_1 = last(x$AGE_2), .after = Inf)
}

dat |> 
  group_split(S.NO) |> 
  purrr::map_dfr(pad_rows)
#> # A tibble: 15 × 3
#>     S.NO AGE_1 AGE_2
#>    <int> <int> <int>
#>  1   123    NA    19
#>  2   123    19    24
#>  3   123    24    NA
#>  4   124    NA    18
#>  5   124    18    21
#>  6   124    21    28
#>  7   124    28    35
#>  8   124    35    NA
#>  9   125    NA    13
#> 10   125    13    19
#> 11   125    19    23
#> 12   125    23    NA
#> 13   126    NA    19
#> 14   126    19    21
#> 15   126    21    NA

• • 数据**

dat <- data.frame(
        S.NO = c(123L, 124L, 124L, 124L, 125L, 125L, 126L),
       AGE_1 = c(19L, 18L, 21L, 28L, 13L, 19L, 19L),
       AGE_2 = c(24L, 21L, 28L, 35L, 19L, 23L, 21L)
)

使用group_modify

library(dplyr)
library(tibble)
df %>% 
  group_by(S.NO) %>% 
  group_modify(~ .x %>% 
                add_row(AGE_2= first(.x$AGE_1), .before = 1) %>% 
                add_row(AGE_1 = last(.x$AGE_2))) %>% 
  ungroup

• 输出

# A tibble: 15 × 3
    S.NO AGE_1 AGE_2
   <int> <int> <int>
 1   123    NA    19
 2   123    19    24
 3   123    24    NA
 4   124    NA    18
 5   124    18    21
 6   124    21    28
 7   124    28    35
 8   124    35    NA
 9   125    NA    13
10   125    13    19
11   125    19    23
12   125    23    NA
13   126    NA    19
14   126    19    21
15   126    21    NA

使用nest_by的方法

library(dplyr)
library(tidyr) # unnest

df %>% 
  nest_by(S.NO) %>% 
  mutate(data = list(unique(unlist(data)))) %>% 
  unnest(data) %>% 
  group_by(S.NO) %>% 
  reframe(AGE_1 = c(NA, data), AGE_2 = c(data, NA))
# A tibble: 15 × 3
    S.NO AGE_1 AGE_2
   <int> <int> <int>
 1   123    NA    19
 2   123    19    24
 3   123    24    NA
 4   124    NA    18
 5   124    18    21
 6   124    21    28
 7   124    28    35
 8   124    35    NA
 9   125    NA    13
10   125    13    19
11   125    19    23
12   125    23    NA
13   126    NA    19
14   126    19    21
15   126    21    NA

数据

df <- structure(list(S.NO = c(123L, 124L, 124L, 124L, 125L, 125L, 126L
), AGE_1 = c(19L, 18L, 21L, 28L, 13L, 19L, 19L), AGE_2 = c(24L, 
21L, 28L, 35L, 19L, 23L, 21L)), class = "data.frame", row.names = c(NA, 
-7L))